[petsc-dev] [petsc-maint #72279] PETSc and multigpu
Victor Minden
victorminden at gmail.com
Sun May 8 16:26:53 CDT 2011
Barry,
I can verify this on breadboard now,
with two processes, cuda
minden at bb45:~/petsc-dev/src/snes/examples/tutorials$
/home/balay/soft/mvapich2-1.5-lucid/bin/mpiexec.hydra -machinefile
/home/balay/machinefile -n 2 ./ex47cu -da_grid_x 65535 -log_summary
-snes_monitor -ksp_monitor -da_vec_type cusp
0 SNES Function norm 3.906279802209e-03
0 KSP Residual norm 5.994156809227e+00
1 KSP Residual norm 5.927247846249e-05
1 SNES Function norm 3.906225077938e-03
0 KSP Residual norm 5.993813868985e+00
1 KSP Residual norm 5.927575078206e-05
terminate called after throwing an instance of 'thrust::system::system_error'
what(): invalid device pointer
terminate called after throwing an instance of 'thrust::system::system_error'
what(): invalid device pointer
Aborted (signal 6)
Without cuda
minden at bb45:~/petsc-dev/src/snes/examples/tutorials$
/home/balay/soft/mvapich2-1.5-lucid/bin/mpiexec.hydra -machinefile
/home/balay/machinefile -n 2 ./ex47cu -da_grid_x 65535 -log_summary
-snes_monitor -ksp_monitor
0 SNES Function norm 3.906279802209e-03
0 KSP Residual norm 5.994156809227e+00
1 KSP Residual norm 3.538158441448e-04
2 KSP Residual norm 3.124431921666e-04
3 KSP Residual norm 4.109213410989e-06
1 SNES Function norm 7.201017610490e-04
0 KSP Residual norm 3.317803708316e-02
1 KSP Residual norm 2.447380361169e-06
2 KSP Residual norm 2.164193969957e-06
3 KSP Residual norm 2.124317398679e-08
2 SNES Function norm 1.719678934825e-05
0 KSP Residual norm 1.651586453143e-06
1 KSP Residual norm 2.037037536868e-08
2 KSP Residual norm 1.109736798274e-08
3 KSP Residual norm 1.857218772156e-12
3 SNES Function norm 1.159391068583e-09
0 KSP Residual norm 3.116936044619e-11
1 KSP Residual norm 1.366503312678e-12
2 KSP Residual norm 6.598477672192e-13
3 KSP Residual norm 5.306147277879e-17
4 SNES Function norm 2.202297235559e-10
Note the repeated norms when using cuda. Looks like I'll have to take
a closer look at this.
-Victor
---
Victor L. Minden
Tufts University
School of Engineering
Class of 2012
On Thu, May 5, 2011 at 2:57 PM, Barry Smith <bsmith at mcs.anl.gov> wrote:
>
> Alexander
>
> Thank you for the sample code; it will be very useful.
>
> We have run parallel jobs with CUDA where each node has only a single MPI process and uses a single GPU without the crash that you get below. I cannot explain why it would not work in your situation. Do you have access to two nodes each with a GPU so you could try that?
>
> It is crashing in a delete of a
>
> struct _p_PetscCUSPIndices {
> CUSPINTARRAYCPU indicesCPU;
> CUSPINTARRAYGPU indicesGPU;
> };
>
> where cusp::array1d<PetscInt,cusp::device_memory>
>
> thus it is crashing after it has completed actually doing the computation. If you run with -snes_monitor -ksp_monitor with and without the -da_vec_type cusp on 2 processes what do you get for output in the two cases? I want to see if it is running correctly on two processes?
>
> Could the crash be due to memory corruption sometime doing the computation?
>
>
> Barry
>
>
>
>
>
> On May 5, 2011, at 3:38 AM, Alexander Grayver wrote:
>
>> Hello!
>>
>> We work with petsc-dev branch and ex47cu.cu example. Our platform is
>> Intel Quad processor and 8 identical Tesla GPUs. CUDA 3.2 toolkit is
>> installed.
>> Ideally we would like to make petsc working in a multi-GPU way within
>> just one node so that different GPUs could be attached to different
>> processes.
>> Since it's not possible within current PETSc implementation we created a
>> preload library (see LD_PRELOAD for details) for CUBLAS function
>> cublasInit().
>> When PETSc calls this function our library gets control and we assign
>> GPUs according to rank within MPI communicator, then we call original
>> cublasInit().
>> This preload library is very simple, see petsc_mgpu.c attached.
>> This trick makes each process to have its own context and ideally all
>> computations should be distributed over several GPUs.
>>
>> We managed to build petsc and example (see makefile attached) and we
>> tested it as follows:
>>
>> [agraiver at tesla-cmc new]$ ./lapexp -da_grid_x 65535 -info > cpu_1process.out
>> [agraiver at tesla-cmc new]$ mpirun -np 2 ./lapexp -da_grid_x 65535 -info >
>> cpu_2processes.out
>> [agraiver at tesla-cmc new]$ ./lapexp -da_grid_x 65535 -da_vec_type cusp
>> -info > gpu_1process.out
>> [agraiver at tesla-cmc new]$ mpirun -np 2 ./lapexp -da_grid_x 65535
>> -da_vec_type cusp -info > gpu_2processes.out
>>
>> Everything except last configuration works well. The last one crashes
>> with the following exception and callstack:
>> terminate called after throwing an instance of
>> 'thrust::system::system_error'
>> what(): invalid device pointer
>> [tesla-cmc:15549] *** Process received signal ***
>> [tesla-cmc:15549] Signal: Aborted (6)
>> [tesla-cmc:15549] Signal code: (-6)
>> [tesla-cmc:15549] [ 0] /lib64/libpthread.so.0() [0x3de540eeb0]
>> [tesla-cmc:15549] [ 1] /lib64/libc.so.6(gsignal+0x35) [0x3de50330c5]
>> [tesla-cmc:15549] [ 2] /lib64/libc.so.6(abort+0x186) [0x3de5034a76]
>> [tesla-cmc:15549] [ 3]
>> /opt/llvm/dragonegg/lib64/libstdc++.so.6(_ZN9__gnu_cxx27__verbose_terminate_handlerEv+0x11d)
>> [0x7f0d3530b95d]
>> [tesla-cmc:15549] [ 4]
>> /opt/llvm/dragonegg/lib64/libstdc++.so.6(+0xb7b76) [0x7f0d35309b76]
>> [tesla-cmc:15549] [ 5]
>> /opt/llvm/dragonegg/lib64/libstdc++.so.6(+0xb7ba3) [0x7f0d35309ba3]
>> [tesla-cmc:15549] [ 6]
>> /opt/llvm/dragonegg/lib64/libstdc++.so.6(+0xb7cae) [0x7f0d35309cae]
>> [tesla-cmc:15549] [ 7]
>> ./lapexp(_ZN6thrust6detail6device4cuda4freeILj0EEEvNS_10device_ptrIvEE+0x69)
>> [0x426320]
>> [tesla-cmc:15549] [ 8]
>> ./lapexp(_ZN6thrust6detail6device8dispatch4freeILj0EEEvNS_10device_ptrIvEENS0_21cuda_device_space_tagE+0x2b)
>> [0x4258b2]
>> [tesla-cmc:15549] [ 9]
>> ./lapexp(_ZN6thrust11device_freeENS_10device_ptrIvEE+0x2f) [0x424f78]
>> [tesla-cmc:15549] [10]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(_ZN6thrust23device_malloc_allocatorIiE10deallocateENS_10device_ptrIiEEm+0x33)
>> [0x7f0d36aeacff]
>> [tesla-cmc:15549] [11]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(_ZN6thrust6detail18contiguous_storageIiNS_23device_malloc_allocatorIiEEE10deallocateEv+0x6e)
>> [0x7f0d36ae8e78]
>> [tesla-cmc:15549] [12]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(_ZN6thrust6detail18contiguous_storageIiNS_23device_malloc_allocatorIiEEED1Ev+0x19)
>> [0x7f0d36ae75f7]
>> [tesla-cmc:15549] [13]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(_ZN6thrust6detail11vector_baseIiNS_23device_malloc_allocatorIiEEED1Ev+0x52)
>> [0x7f0d36ae65f4]
>> [tesla-cmc:15549] [14]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(_ZN4cusp7array1dIiN6thrust6detail21cuda_device_space_tagEED1Ev+0x18)
>> [0x7f0d36ae5c2e]
>> [tesla-cmc:15549] [15]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(_ZN19_p_PetscCUSPIndicesD1Ev+0x1d) [0x7f0d3751e45f]
>> [tesla-cmc:15549] [16]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(PetscCUSPIndicesDestroy+0x20f)
>> [0x7f0d3750c840]
>> [tesla-cmc:15549] [17]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(VecScatterDestroy_PtoP+0x1bc8)
>> [0x7f0d375af8af]
>> [tesla-cmc:15549] [18]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(VecScatterDestroy+0x586)
>> [0x7f0d375e9ddf]
>> [tesla-cmc:15549] [19]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(MatDestroy_MPIAIJ+0x49f)
>> [0x7f0d37191d24]
>> [tesla-cmc:15549] [20]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(MatDestroy+0x546) [0x7f0d370d54fe]
>> [tesla-cmc:15549] [21]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(SNESReset+0x5d1) [0x7f0d3746fac3]
>> [tesla-cmc:15549] [22]
>> /opt/openmpi_gcc-1.4.3/lib/libpetsc.so(SNESDestroy+0x4b8) [0x7f0d37470210]
>> [tesla-cmc:15549] [23] ./lapexp(main+0x5ed) [0x420745]
>>
>> I've sent all detailed output files for different execution
>> configuration listed above as well as configure.log and make.log to
>> petsc-maint at mcs.anl.gov hoping that someone could recognize the problem.
>> Now we have one node with multi-GPU, but I'm also wondering if someone
>> really tested usage of GPU functionality over several nodes with one GPU
>> each?
>>
>> Regards,
>> Alexander
>>
>> <petsc_mgpu.c><makefile.txt><configure.log>
>
>
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